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mlem.api.serve()

Serve a model by exposing its methods as endpoints.

def serve(
    model: Union[str, MlemModel],
    server: Union[Server, str],
    **server_kwargs,
)

Usage:

from mlem.api import serve

serve(model, "fastapi")

Description

This API is the underlying mechanism for the mlem serve command and allows us to locally serve a model by exposing its methods as endpoints. This makes it possible to easily make requests (for inference or otherwise) against the served model.

Parameters

  • model (required) - The model to serve.
  • server (required) - Out-of-the-box supported one is "fastapi".
  • server_kwargs (required) - Additional kwargs to pass to the server.

Returns

None

Exceptions

None

Examples

from sklearn.datasets import load_iris
from sklearn.tree import DecisionTreeClassifier

from mlem.core.objects import MlemModel
from mlem.contrib.fastapi import FastAPIServer
from mlem.api import serve

train, target = load_iris(return_X_y=True)
model = DecisionTreeClassifier().fit(train, target)
m = MlemModel.from_obj(model, sample_data=train)

server_obj = FastAPIServer(port=9000)
serve(m, server_obj)
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